Triple

T6476849
Position Surface form Disambiguated ID Type / Status
Subject Harry Christopher Carabina E146092 entity
Predicate notableEmployer P20563 FINISHED
Object WGN-TV E253579 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: WGN-TV | Statement: [Harry Christopher Carabina, notableEmployer, WGN-TV]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WGN-TV
Context triple: [Harry Christopher Carabina, notableEmployer, WGN-TV]
  • A. WGN-TV chosen
    WGN-TV is a Chicago-based television station and former national superstation known for its local news, sports broadcasts, and syndicated programming.
  • B. WGN
    WGN is the National Rail station code for Wigan North Western railway station in Greater Manchester, England.
  • C. WGN America
    WGN America is a U.S.-based cable television network known for airing syndicated series, movies, and original programming to a national audience.
  • D. WGN Radio
    WGN Radio is a historic Chicago-based AM radio station known for its news, talk, and sports programming and long association with the Chicago Tribune.
  • E. GMA News TV
    GMA News TV is a Philippine free-to-air television network known for its news, public affairs, and informational programming.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69c008fec7408190af7b146dc63d9750 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a4ba9588190a965b9e7feb7e598 completed March 22, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c653a7f348819091bca6b582ad230d completed March 27, 2026, 9:53 a.m.
Created at: March 22, 2026, 4:51 p.m.